27 July 1999 Real-time moving target detection based on a nonlinear filter using short-time and medium-time image differences
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Abstract
Motion is one of the most important cues for the acquisition of targets. Given the real time requirement, there are two basic approaches for the detection of motion: (1) The difference between the actual image and an adaptive background image and (2) The difference between the actual image and preceding images. The first approach provides a precise and robust segmentation of the moving targets from the background and works well with low target/background contrast and clutter. However, when the sight is moving the background changes too quickly for a robust calculation of a valid background image. The second approach adapts well to the actual environment, but provides only an inaccurate indication of the moving edges of the targets and is quite sensitive to target/background contrast and clutter. This work presents a new approach which combines in a nonlinear manner the short time and the medium time image differences between the actual image and preceding images. It provides a precise and robust segmentation of the moving targets from the background and a good adaptation to the actual environment. In addition, it works even better than the first approach for low target/background contrast and clutter. We present the details of this approach including its real time implementation and its role in our Automatic Target Detection and Tracking system.
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Holger Lange, Holger Lange, } "Real-time moving target detection based on a nonlinear filter using short-time and medium-time image differences", Proc. SPIE 3720, Signal Processing, Sensor Fusion, and Target Recognition VIII, (27 July 1999); doi: 10.1117/12.357160; https://doi.org/10.1117/12.357160
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